One of the most difficult problems in the field of genomics is assembling relatively short "reads" of DNA into complete chromosomes. In a new paper published in Proceedings of the National Academy of Sciences an interdisciplinary group of genome and computer scientists has solved this problem, creating an algorithm that can rapidly create "virtual chromosomes" with no prior information about how the genome is organized.
The powerful DNA sequencing methods developed about 15 years ago, known as next generation sequencing (NGS) technologies, create thousands of short fragments. In species whose genetics has already been extensively studied, existing information can be used to organize and order the NGS fragments, rather like using a sketch of the complete picture as a guide to a jigsaw puzzle. But as genome scientists push into less-studied species, it becomes more difficult to finish the puzzle.
To solve this problem, a team led by Harris Lewin, distinguished professor of evolution and ecology and vice chancellor for research at the University of California, Davis and Jian Ma, assistant professor at the University of Illinois at Urbana-Champaign created a computer algorithm that uses the known chromosome organization of one or more known species and NGS information from a newly sequenced genome to create virtual chromosomes.
"We show for the first time that chromosomes can be assembled from NGS data without the aid of a preexisting genetic or physical map of the genome," Lewin said. The new algorithm will be very useful for large-scale sequencing projects such as G10K, an effort to sequence 10,000 vertebrate genomes of which very few have a map, Lewin said.
"As we have shown previously, there is much to learn about phenotypic evolution from understanding how chromosomes are organized in one species relative to other species," he said. The algorithm is called RACA (for reference-assisted chromosome assembly), co-developed by Jaebum Kim, now at Konkuk University, South Korea, and Denis Larkin of Aberystwyth University, Wales. Kim wrote the software tool which was evaluated using simulated data, standardized reference genome datasets as well as a primary NGS assembly of the newly sequenced Tibetan antelope genome generated by BGI (Shenzhen, China) in collaboration with Professor Ri-Li Ge at Qinghai University, China.
Larkin led the experimental validation, in collaboration with scientists at BGI, proving that predictions of chromosome organization were highly accurate. Ma said that the new RACA algorithm will perform even better as developing NGS technologies produce longer reads of DNA sequence. "Even with what is expected from the newest generation of sequencers, complete chromosome assemblies will always be a difficult technical issue, especially for complex genomes. RACA predictions address this problem and can be incorporated into current NGS assembly pipelines," Ma said.
Niels Bohr and Max Delbruck believed that complementarity—such as wave–particle duality—was not limited to the quantum realm, but had correlates in the study of living things. Biological complementarity would indicate that no single technique or perspective allows comprehensive viewing of all of a biological entity's complete qualities and behaviors; instead, complementary perspectives, necessarily and irrevocably excluding all others at the moment an experimental approach is selected, would be necessary to understand the whole. Systems biology and complexity theory reveal that, as in the quantum realm, experimental observations themselves limit our capacity to understand a biological system completely because of scale-dependent “horizons of knowledge,” a form of biological complementarity as predicted by Bohr and Delbruck. Specifically, observational selection is inherently, irreducibly coupled to observed biological systems as in the quantum realm. These nested systems, beginning with biomolecules in aqueous solution all the way up to the global ecosystem itself, are understood as a seamless whole operating simultaneously and complementarily at various levels. This selection of an observational stance is inseparable from descriptions of biology indicates—in accordance with views of thinkers such as von Neumann, Wigner, and Stapp—that even at levels of scale governed by classical physics, at biological scales, observational choice remains inextricably woven into the establishment, in the observational moment, of the present conditions of existence. These conceptual shifts will not only have theoretical impact, but may point the way to new, successful therapeutic interventions, medically (at the scale of organisms) or environmentally/economically (at a global scale).
Molecular Systems Biology is a peer-reviewed author-pays online journal that publishes full-length papers and accompanying synopses describing original research in the field of molecular systems biology and which focuses on the analysis,...
Tzu-ching Wu's insight:
New technologies are pushing the limits of biological measurements in terms of scale, resolution and accuracy, which is enabling the engineering of living organisms in unprecedented ways. Increasingly sophisticated computational methods are used to analyze and integrate quantitative and large-scale biological data. This series features Reviews on the technological platforms and methodologies that are driving the fields of systems and synthetic biology forward to reach new frontiers in biology.
To mark our tenth Anniversary at PLOS Biology, we are launching a special, celebratory Tenth Anniversary PLOS Biology Collection which showcases 10 specially selected PLOS Biology research articles drawn from a decade of publishing excellent science. It also features newly commissioned articles, including thought-provoking pieces on the Open Access movement (past and present), on article-level metrics, and on the history of the Public Library of Science. Each research article highlighted in the collection is also accompanied by a PLOS Biologue blog post to extend the impact of these remarkable studies to the widest possible audience.
Biologists of the University of Zurich have developed a method to visualize the activity of genes in single cells. The method is so efficient that, for the first time, a thousand genes can be studied in parallel in ten thousand single human cells.
Applications lie in fields of basic research and medical diagnostics. The new method shows that the activity of genes, and the spatial organization of the resulting transcript molecules, strongly vary between single cells. Whenever cells activate a gene, they produce gene specific transcript molecules, which make the function of the gene available to the cell. The measurement of gene activity is a routine activity in medical diagnostics, especially in cancer medicine. Today's technologies determine the activity of genes by measuring the amount of transcript molecules. However, these technologies can neither measure the amount of transcript molecules of one thousand genes in ten thousand single cells, nor the spatial organization of transcript molecules within a single cell. The fully automated procedure, developed by biologists of the University of Zurich under the supervision of Prof. Lucas Pelkmans, allows, for the first time, a parallel measurement of the amount and spatial organization of single transcript molecules in ten thousands single cells. The results, which were recently published in the scientific journal Nature Methods, provide completely novel insights into the variability of gene activity of single cells.
The method developed by Pelkmans' PhD students Nico Battich and Thomas Stoeger is based upon the combination of robots, an automated fluorescence microscope and a supercomputer. "When genes become active, specific transcript molecules are produced. We can stain them with the help of a robot", explains Stoeger. Subsequently, fluorescence microscope images of brightly glowing transcript molecules are generated. Those images were analyzed with the supercomputer Brutus, of the ETH Zurich. With this method, one thousand human genes can be studied in ten thousand single cells. According to Pelkmans, the advantages of this method are the high number of single cells and the possibility to study, for the first time, the spatial organization of the transcript molecules of many genes.
The analysis of the new data shows that individual cells distinguish themselves in the activity of their genes. While the scientists had been suspecting a high variability in the amount of transcript molecules, they were surprised to discover a strong variability in the spatial organization of transcript molecules within single cells and between multiple single cells. The transcript molecules adapted distinctive patterns.
The importance of these new insights was summarized by Pelkmans: "Our method will be of importance to basic research and the understanding of cancer tumors because it allows us to map the activity of genes within single tumor cells.
Our understanding of the forms, functions, and movement of RNA continues to expand. Not only can RNA control gene expression by multiple mechanisms within a cell, it appears to travel outside the cell within an organism as well. This raises the interesting question of whether the RNA world extends beyond the boundaries of the organism. Can RNA traffic integrate an organism into its environment—is there “social RNA”? Examining the mechanism of RNA interference (RNAi) may be a good route for seeking the answer.
We introduce an automated method for the bottom-up reconstruction of the cognitive evolution of science, based on big-data issued from digital libraries, and modeled as lineage relationships between scientific fields. We refer to these dynamic structures as phylomemetic networks or phylomemies, by analogy with biological evolution; and we show that they exhibit strong regularities, with clearly identifiable phylomemetic patterns. Some structural properties of the scientific fields - in particular their density -, which are defined independently of the phylomemy reconstruction, are clearly correlated with their status and their fate in the phylomemy (like their age or their short term survival). Within the framework of a quantitative epistemology, this approach raises the question of predictibility for science evolution, and sketches a prototypical life cycle of the scientific fields: an increase of their cohesion after their emergence, the renewal of their conceptual background through branching or merging events, before decaying when their density is getting too low.
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